根据pandas.DataFrame中的值更改seaborn.catplot标记颜色亮度

Question

我尝试用包含多个基数（a、C、G、T、U^{1和U2）的数据的pd.DataFrame图创建一个sns.catplot图。
我的目标是只绘制由df ['environment']值决定亮度的标记，因此没有线条、方框或任何东西。我也尝试了一些cycler.cycler (color = colourlist)的东西，但是“情节不想选择”超过三种颜色}

import matplotlib.pyplot as plt
import matplotlib
import seaborn as sns
import pandas as pd
import numpy as np
import cycler
import os

sns.set (style = 'white', color_codes = True, palette = ["#FF0000", "#0000FF", "#00FF00", "#C03030", "#3030C0", "#30C030"])

colourlist = np.array ([ [0, 0, 0] ])
for v in [0, 45] :
    for s in [0, 45] :
        for h in [0, 120, 240] :
            try :
                H, S, V = h / 360., (100 - s) / 100., (100 - v) / 100.
                colourlist = np.append (colourlist, [ [H, S, V] ], axis = 0)
            except :
                pass
colourlist = np.delete (colourlist, 0, 0)

matplotlib.rcParams ['axes.prop_cycle'] = cycler.cycler (color = colourlist)
matplotlib.rcParams ['image.cmap'] = 'hsv'
matplotlib.rcParams ['savefig.transparent'] = True
matplotlib.rcParams ['savefig.format'] = 'eps'
matplotlib.rcParams ['axes.xmargin'] = 0
matplotlib.rcParams ['axes.ymargin'] = 0
matplotlib.rcParams ['figure.frameon'] = False
matplotlib.spines.rcParams ['axes.spines.right'] = False
matplotlib.spines.rcParams ['axes.spines.top'] = False
matplotlib.rcParams ['xtick.bottom'] = True
matplotlib.rcParams ['ytick.left'] = True

file = os.path.join (os.environ ['HOME'], 'Data.csv')
with open (file, 'r') as f :
    df = pd.read_csv (f, index_col = 0, header = 0, thousands = None, decimal = '.')
df ['base'] = df ['base'].str.upper ()
#df ['method'] = df ['method'].str.upper ()
df = df.sort_values (['charge', 'base', 'environment'])

sns.catplot (jitter = False, data = df, x = 'base', y = 'energy', hue = 'charge', palette = ["#000FFF", "#00FF00", "#FF0000", "#00FFFF", "#FF00FF", "#FFFF00"], order = ['A', 'C', 'U1', '', 'G', 'T', 'U2'])

~/Data.csv：

,environment,base,charge,energy,method
0,pbs,A,neg,0.34835,1
1,pbs,C,neg,0.40194,2
2,pbs,G,neg,0.34959,1
3,pbs,T,neg,0.40738,2
4,pbs,U1,neg,0.34904,2
5,pbs,U2,neg,0.40016,2
6,pbs,A,neu,0.40151,3
7,pbs,C,neu,0.34494,3
8,pbs,G,neu,0.40193,3
9,pbs,T,neu,0.34458,3
10,pbs,U1,neu,0.34646,3
11,pbs,U2,neu,0.40871,3
12,pbs,A,pos,0.34047,2
13,pbs,C,pos,0.40157,2
14,pbs,G,pos,0.34232,2
15,pbs,T,pos,0.40854,2
16,pbs,U1,pos,0.34611,2
17,pbs,U2,pos,0.34414,2
18,polymeric,A,neg,0.28333,2
19,polymeric,C,neg,0.46908,3
20,polymeric,G,neg,0.33224,3
21,polymeric,T,neg,0.35825,1
22,polymeric,U1,neg,0.33033,3
23,polymeric,U2,neg,0.39167,3
24,polymeric,A,neu,0.36964,2
25,polymeric,C,neu,0.33979,2
26,polymeric,G,neu,0.41815,3
27,polymeric,T,neu,0.30786,2
28,polymeric,U1,neu,0.40727,1
29,polymeric,U2,neu,0.36719,3
30,polymeric,A,pos,0.38173,1
31,polymeric,C,pos,0.35060,3
32,polymeric,G,pos,0.37617,1
33,polymeric,T,pos,0.44172,2
34,polymeric,U1,pos,0.31267,3
35,polymeric,U2,pos,0.34478,2

我想到了类似的事情

sns.scatterplot (data = df, x = 'base', y = 'energy', hue = 'charge', x_order = ['A', 'C', 'U1', '', 'G', 'T', 'U2'], brightness = np.where (df ['environment'] == 'pbs', 1., .5) ).

我可以用matplotlib来绘制这个（数据；pandas.DataFrame）吗？代码是什么样子的